MCPcopy Create free account

hub / github.com/andersbll/nnet / functions

Functions64 in github.com/andersbll/nnet

⨍ Functions 64◇ Types & classes 10
↓ 4 callersMethoderror
Calculate error on the given data.
nnet/neuralnetwork.py:79
↓ 4 callersMethodfprop
Calculate layer output for given input (forward propagation).
nnet/layers.py:10
↓ 3 callersMethodfit
Train network on the given data.
nnet/neuralnetwork.py:25
↓ 2 callersMethod_loss
(self, X, Y_one_hot)
nnet/neuralnetwork.py:64
↓ 2 callersMethod_setup
(self, X, Y)
nnet/neuralnetwork.py:14
↓ 2 callersMethodbprop
Calculate input gradient.
nnet/layers.py:14
↓ 2 callersMethodinput_grad
Calculate input gradient given output and predicted output.
nnet/layers.py:31
↓ 2 callersFunctionone_hot
(labels)
nnet/helpers.py:4
↓ 2 callersMethodoutput_shape
(self, input_shape)
nnet/convnet/layers.py:87
↓ 2 callersMethodparams
(self)
nnet/layers.py:72
↓ 1 callersMethodcheck_gradients
Helper function to test the parameter gradients for correctness.
nnet/neuralnetwork.py:85
↓ 1 callersMethodfun
(param_new)
nnet/neuralnetwork.py:97
↓ 1 callersMethodloss
Calculate mean loss given output and predicted output.
nnet/layers.py:27
↓ 1 callersMethodoutput_shape
Calculate shape of this layer's output. input_shape[0] is the number of samples in the input. input_shape[1:] is the shape of the fea
nnet/layers.py:18
↓ 1 callersMethodoutput_shape
(self, input_shape)
nnet/convnet/layers.py:53
↓ 1 callersMethodparam_grads
(self)
nnet/layers.py:78
↓ 1 callersMethodparam_incs
(self)
nnet/layers.py:75
↓ 1 callersMethodpredict
Calculate an output Y for the given input X.
nnet/neuralnetwork.py:71
↓ 1 callersFunctionread
(fname)
setup.py:9
↓ 1 callersFunctionrun
()
examples/cnn_mnist.py:10
↓ 1 callersFunctionrun
()
examples/mlp_mnist.py:10
↓ 1 callersFunctionrun
()
examples/mlp.py:9
↓ 1 callersFunctionsigmoid
(x)
nnet/helpers.py:17
↓ 1 callersFunctiontest_conv
()
nnet/convnet/test_conv.py:9
↓ 1 callersFunctiontest_pool
()
nnet/convnet/test_pool.py:8
↓ 1 callersFunctionunhot
(one_hot_labels)
nnet/helpers.py:13
Method__init__
(self, layers, rng=None)
nnet/neuralnetwork.py:8
Method__init__
(self, n_out, weight_scale, weight_decay=0.0)
nnet/layers.py:51
Method__init__
(self, type)
nnet/layers.py:88
Method__init__
(self, n_feats, filter_shape, strides, weight_scale, weight_decay=0.0, padding_mode='same', b
nnet/convnet/layers.py:9
Method__init__
(self, pool_shape=(3, 3), strides=(1, 1), mode='max')
nnet/convnet/layers.py:68
Method_setup
Setup layer with parameters that are unknown at __init__().
nnet/layers.py:6
Method_setup
(self, input_shape, rng)
nnet/layers.py:56
Method_setup
(self, input_shape, rng)
nnet/convnet/layers.py:19
Methodbprop
(self, output_grad)
nnet/layers.py:66
Methodbprop
(self, output_grad)
nnet/layers.py:105
Methodbprop
(self, output_grad)
nnet/layers.py:118
Methodbprop
(self, output_grad)
nnet/convnet/layers.py:32
Methodbprop
(self, output_grad)
nnet/convnet/layers.py:82
Methodbprop
(self, output_grad)
nnet/convnet/layers.py:100
Methodfprop
(self, input)
nnet/layers.py:62
Methodfprop
(self, input)
nnet/layers.py:101
Methodfprop
(self, input)
nnet/layers.py:114
Methodfprop
(self, input)
nnet/convnet/layers.py:25
Methodfprop
(self, input)
nnet/convnet/layers.py:73
Methodfprop
(self, input)
nnet/convnet/layers.py:96
Methodgrad_fun
(param_new)
nnet/neuralnetwork.py:101
Methodinput_grad
(self, Y, Y_pred)
nnet/layers.py:124
Methodloss
(self, Y, Y_pred)
nnet/layers.py:128
Methodoutput_shape
(self, input_shape)
nnet/layers.py:83
Methodoutput_shape
(self, input_shape)
nnet/layers.py:108
Methodoutput_shape
(self, input_shape)
nnet/layers.py:136
Methodoutput_shape
(self, input_shape)
nnet/convnet/layers.py:103
Methodparam_grads
Get layer parameter gradients as calculated from bprop().
nnet/layers.py:41
Methodparam_grads
(self)
nnet/convnet/layers.py:48
Methodparam_incs
Get layer parameter steps as calculated from bprop().
nnet/layers.py:45
Methodparam_incs
(self)
nnet/convnet/layers.py:45
Methodparams
Layer parameters.
nnet/layers.py:37
Methodparams
(self)
nnet/convnet/layers.py:42
Functionrelu
(x)
nnet/helpers.py:35
Functionrelu_d
(x)
nnet/helpers.py:39
Functionsigmoid_d
(x)
nnet/helpers.py:21
Functiontanh
(x)
nnet/helpers.py:26
Functiontanh_d
(x)
nnet/helpers.py:30